The long-term objective of this project is to develop novel and powerful statistical methods to identify genes underlying complex traits. With the availability of large numbers of genetic markers in the human genome, it is becoming feasible in genetic association studies to genotype thousands of markers and to saturate candidate regions with many tightly linked markers. The analysis of such data poses challenging statistical issues and both theoretical and empirical studies are needed to develop and evaluate statistical methods that can best extract the most relevant information. The specific aims of this projects are: (1) Develop statistical methods to appropriately control for population stratification in an association study, both for qualitative traits and for quantitative traits; (2) Develop statistical methods to study associations between multiple tightly linked markers and complex traits of interest, both for samples consisting of unrelated individuals and for samples consisting of pedigrees; (3) Compare statistical efficiencies and the overall cost for various genotyping strategies in association studies; and (4) Develop computer programs that implement the statistical methods developed in this project and distribute them to the scientific community. We will also apply these methods to map complex disease genes through our extensive collaborations. The developments of these novel statistical methods and user-friendly computer programs will provide biomedical researchers with important tools to identify genes underlying complex traits .